An AI agency's 1-year postmortem: what AI customer support actually fixed
Warm-Reaction-456 · reddit · 2026-09-12
An AI agency reviews a support-inbox AI system built for an e-commerce client a year ago, now handling about three quarters of tickets.
What paid off (in order):
- Self-service that isn't a phone tree: a model trained on the client's own help docs and order data survives customers changing subjects; the key safety feature is an escalation gate that routes low-confidence cases to humans with a summary — cleaning up after a confident wrong-answer bot costs more than building it right.
- Faster humans: putting a model in front of the knowledge base returns summarized answers while the customer is still typing; AI-drafted replies scored higher satisfaction, partly because they "never forget to apologize."
- Whole-operation visibility: weekly reads of every transcript reveal which ticket types take longest and where complaints cluster, so product/marketing fix root causes; also drafts after-call summaries and lets conversations flow across Instagram DMs and email without repetition.
What it didn't fix: a bad returns policy — AI just delivers bad news faster, and month one is messy. Model deprecations, stale docs and silent supplier changes require ongoing maintenance, hence retainers instead of projects.
Process advice: decide the experience first, then channels, then platform, then design the journey end to end.
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